Some parameters are confused for training wider face

Thanks for your code, but I am confused about some parameters during training wider face. In the code,
1. end_epoch=10000, lr_steps=[55,68,80]; I am not sure it is correct or not for training wider face, because it means the last 9920 epochs are using lr of 0.0.000004?
2. opt = optimizer.SGD(learning_rate=lr, momentum=0.9, wd=0.0005, rescale_grad=1.0/len(ctx), clip_gradient=None), the rescale_grad should be 1.0/len(ctx)/batch_size?
3. During training, it fixed parameters of conv1, conv2, conv2, upsampling, it is correct?
4. How long you train the wider face dataset? how many gpus? what is the dataset?
Any advice will be appreciated. thanks.